diff --git a/src/main/java/com/gunshi/project/xyt/model/ForecastUseparam.java b/src/main/java/com/gunshi/project/xyt/model/ForecastUseparam.java
index ddc0a08..5376ee6 100644
--- a/src/main/java/com/gunshi/project/xyt/model/ForecastUseparam.java
+++ b/src/main/java/com/gunshi/project/xyt/model/ForecastUseparam.java
@@ -79,7 +79,7 @@ public class ForecastUseparam extends GenericPageParams implements Serializable
         /**
         * 参数描述
         */
-        @TableField(value="param_remarks")
+        @TableField(value="param_desc")
         @Schema(description="参数描述")
         @Size(max = 255,message = "参数描述最大长度要小于 255")
         private String paramDesc;
diff --git a/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java b/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java
index 86b3bd1..4975232 100644
--- a/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java
+++ b/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java
@@ -14,8 +14,8 @@ import com.gunshi.project.xyt.grb.RainGrib2Layer;
 import com.gunshi.project.xyt.mapper.ForecastResultsMapper;
 import com.gunshi.project.xyt.model.AttResBase;
 import com.gunshi.project.xyt.model.ForecastPa;
-import com.gunshi.project.xyt.model.ForecastTask;
 import com.gunshi.project.xyt.model.ForecastResults;
+import com.gunshi.project.xyt.model.ForecastTask;
 import com.gunshi.project.xyt.model.ForecastU;
 import com.gunshi.project.xyt.model.ForecastUseparam;
 import com.gunshi.project.xyt.model.StPptnR;
@@ -145,7 +145,7 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
         pptnRAllList.addAll(pptnRExistedList);
         pptnRAllList.addAll(pptnRFutureList);
         // 获取配置参数
-        List<ForecastUseparam> paramList = forecastUseparamService.list();
+        List<ForecastUseparam> paramList = forecastUseparamService.list(new QueryWrapper<ForecastUseparam>().isNotNull("param_code").isNotNull("param_value"));
         List<ForecastU> uList = forecastUService.list();
         if (CollectionUtils.isEmpty(paramList) || CollectionUtils.isEmpty(uList) || CollectionUtils.isEmpty(pptnRAllList)) {
             return voList;
@@ -181,6 +181,9 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
         AttResBase attResBase = attResBaseService.getOne(new QueryWrapper<>());
         // 泄流量
         List<StZqrlB> stZqrlBList = stZqrlBService.list(new QueryWrapper<StZqrlB>().eq("stcd", "716153201"));
+        // 水位历史数据
+        List<StRsvrR> rsvrRRealList = stRsvrRService.list(new QueryWrapper<StRsvrR>().eq("stcd", "716153201").ge("tm", startTime).le("tm", endTime));
+        List<StRsvrR> resultList = reorganizeRsvrRData(rsvrRRealList, dt);
         List<Date[]> periods = splitByDay8To8(startTime, endTime);
         for (Date[] period : periods) {
             // 根据每段时间的开始时间，如果在08点前，则采用前一天的pa值计算
@@ -195,10 +198,10 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
             // 筛选时间段内的降雨数据。第一个条件：时间大于等开始时间；第二个条件：时间小于等于结束时间（不包前但包后，比如从8点开始，就要拆下一个时间：9点的数据）
             List<StPptnR> filterList = pptnRAllList.stream().filter(e -> e.getTm().compareTo(period[0]) >= 0).filter(e -> e.getTm().compareTo(period[1]) <= 0).collect(Collectors.toList());
             // 从第二条数据开始
-            for (int i = 1; i <= filterList.size(); i++) {
+            for (int i = 1; i < filterList.size(); i++) {
+                StPptnR stPptnRLast = filterList.get(i - 1);
                 StPptnR stPptnR = filterList.get(i);
                 String drp = stPptnR.getDrp();
-                StPptnR stPptnRLast = filterList.get(i - 1);
                 // 两条数据的小时差
                 double diffHours = dateHourDifference(stPptnRLast.getTm(), stPptnR.getTm());
                 // 两条数据间需要增补几条
@@ -209,13 +212,12 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
                 }
             }
             double[] PList = pResultList.stream().mapToDouble(Double::parseDouble).toArray();
-            // 水位历史数据
-            List<StRsvrR> rsvrRRealList = stRsvrRService.list(new QueryWrapper<StRsvrR>().eq("stcd", "716153201").ge("tm", period[0]).le("tm", period[1]));
-            rsvrRRealList = reorganizeRsvrRData(rsvrRRealList, dt);
             // 预测执行
             List<FloodAlgorithemVo> forecastVoList = RrainfallForecast.getData(sdf.format(period[0]), forecastPa.getK().doubleValue(), forecastPa.getPa0().doubleValue(), Wm, forecastPa.getPt0().doubleValue(), H1, dt,
                     forecastPa.getPa().doubleValue(), PList, u, "716153201");
             if (CollectionUtils.isNotEmpty(forecastVoList)) {
+                // 筛选同时段的真实水位数据
+                List<StRsvrR> realRsvrList = resultList.stream().filter(item -> item.getTm().compareTo(period[0]) >=0 && item.getTm().compareTo(period[1]) <=0).collect(Collectors.toList());
                 forecastVoList = forecastVoList.subList(0, PList.length);
                 for (int j = 0; j < forecastVoList.size(); j++) {
                     FloodAlgorithemVo floodAlgorithemVo = forecastVoList.get(j);
@@ -226,8 +228,8 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
                     resultVo.setYcCkQValue(floodAlgorithemVo.getCq());// 预测出库流量
                     resultVo.setYcSwHValue(floodAlgorithemVo.getKh());// 预测水库水位
                     H1 = resultVo.getYcSwHValue().doubleValue();// 先以预测水位作为下一次预测段起始值
-                    if (j < rsvrRRealList.size()) {
-                        BigDecimal realSwHValue = new BigDecimal(rsvrRRealList.get(j).getRz());
+                    if (j < realRsvrList.size()) {
+                        BigDecimal realSwHValue = new BigDecimal(realRsvrList.get(j).getRz());
                         resultVo.setRealSwHValue(realSwHValue);// 真实水库水位
                         H1 = realSwHValue.doubleValue();// 如果有真实水位，将最后一条的真实水位作为下一次预测段的初始水位
                         // 真实出库流量=真实水库水位与泄流量曲线差值法
@@ -334,13 +336,14 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
                 // 两条数据的小时差
                 double diffHours = dateHourDifference(stRsvrR.getTm(), stRsvrRNext.getTm());
                 int floorNum = (int) Math.floor(diffHours / dt);
-                BigDecimal meanDifference = new BigDecimal(stRsvrRNext.getRz()).subtract(new BigDecimal(drp)).divide(new BigDecimal(floorNum), BigDecimal.ROUND_HALF_UP, 2);
+                BigDecimal meanDifference = new BigDecimal(stRsvrRNext.getRz()).subtract(new BigDecimal(drp)).divide(new BigDecimal(floorNum), BigDecimal.ROUND_HALF_UP, 3);
                 for (int j = 1; j < floorNum; j++) {
                     // 增补出的数据
                     StRsvrR suppleStRsvrR = new StRsvrR();
-                    BigDecimal add = new BigDecimal(drp).add(meanDifference.multiply(new BigDecimal(j))).setScale(2, BigDecimal.ROUND_HALF_UP);
+                    BigDecimal add = new BigDecimal(drp).add(meanDifference.multiply(new BigDecimal(j))).setScale(3, BigDecimal.ROUND_HALF_UP);
                     try {
-                        suppleStRsvrR.setTm(sdf.parse(RunoffService.calc(sdf.format(tm), hours, minutes, true)));
+                        tm = sdf.parse(RunoffService.calc(sdf.format(tm), hours, minutes, true));
+                        suppleStRsvrR.setTm(tm);
                     } catch (ParseException e) {
                         throw new RuntimeException(e);
                     }
diff --git a/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java b/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java
index 23ec2f6..124d1cd 100644
--- a/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java
+++ b/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java
@@ -71,7 +71,7 @@ public class PaDataTask {
         calendar.setTime(new Date());
         Date nowTime = calendar.getTime();
         // 获取配置参数
-        List<ForecastUseparam> paramList = forecastUseparamService.list();
+        List<ForecastUseparam> paramList = forecastUseparamService.list(new QueryWrapper<ForecastUseparam>().isNotNull("param_code").isNotNull("param_value"));
         List<ForecastK> kList = forecastKService.list();
         // 获取最新pa
         ForecastPa forecastPaLast = forecastPaService.getOne(new QueryWrapper<ForecastPa>().orderBy(true, false, "tm").last("limit 1"));